Dendritic cells loaded with allogeneic tumour cell lysate plus best supportive care versus best supportive care alone in patients with pleural mesothelioma as maintenance therapy after chemotherapy (DENIM): a multicentre, open-label, randomised, phase 2/3 study.

BACKGROUND: Dendritic cell immunotherapy has proven to be safe and induces an immune response in humans. We aimed to establish the efficacy of dendritic cells loaded with allogeneic tumour cell lysate (MesoPher, Amphera BV, 's-Hertogenbosch, Netherlands) as maintenance therapy in patients with pleural mesothelioma. METHODS: In this open-label, randomised, phase 2/3 study, patients with histologically confirmed unresectable pleural mesothelioma, aged 18 years or older, with an Eastern Cooperative Oncology Group performance status score of 0-1, and non-progressing disease after four to six cycles of standard chemotherapy (with pemetrexed 500 mg/m2 plus platinum [cisplatin 75 mg/m2 or carboplatin area under the curve of 5]) were recruited from four centres in Belgium, France, and The Netherlands. Participants were randomly assigned (1:1), using block randomisation (block size of 4), stratified by centre and histology (epithelioid vs other), to MesoPher treatment plus best supportive care or best supportive care alone. Patients received up to a maximum of five MesoPher infusions, with treatment administered on days 1, 15, and 29, and weeks 18 and 30. At each timepoint, participants received an injection of 25 × 106 dendritic cells (two-thirds of the dendritic cells were administered intravenously and a third were injected intradermally). Best supportive care was per local institutional standards. The primary endpoint was overall survival, assessed in all participants randomly assigned to treatment (full analysis set) and safety assessed in all randomly assigned participants, and who underwent leukapheresis if they were in the MesoPher group. This study is registered with ClinicalTrials.gov, NCT03610360, and is closed for accrual. FINDINGS: Between June 21, 2018, and June 10, 2021, 176 patients were screened and randomly assigned to the MesoPher group (n=88) or best supportive care alone group (n=88). One participant in the MesoPher group did not undergo leukapheresis. Mean age was 68 years (SD 8), 149 (85%) of 176 were male, 27 (15%) were female, 173 (98%) were White, two were Asian (1%), and one (1%) was other race. As of data cutoff (June 24, 2023), after a median follow up of 15·1 months (IQR 9·5-22·4), median overall survival was 16·8 months (95% CI 12·4-20·3; 61 [69%] of 88 died) in the MesoPher group and 18·3 months (14·3-21·9; 59 [67%] of 88 died) in the best supportive care group (hazard ratio 1·10 [95% CI 0·77-1·57]; log-rank p=0·62). The most common grade 3-4 treatment-emergent adverse events were chest pain (three [3%] of 87 in the MesoPher group vs two [2%] of 88 in the best supportive care group), dyspnoea (none vs two [2%]), anaemia (two [2%] vs none), nausea (none vs two [2%]), and pneumonia (none vs two [2%]). No deaths due to treatment-emergent adverse events were recorded. Treatment-related adverse events consisted of infusion-related reactions (fever, chills, and fatigue), which occurred in 64 (74%) of 87 patients in the MesoPher group, and injection-site reactions (itch, erythema, and induration), which occurred in 73 (84%) patients, and all were grade 1-2 in severity. No deaths were determined to be treatment related. INTERPRETATION: MesoPher did not show improvement in overall survival in patients with pleural mesothelioma. Immune checkpoint therapy is now standard of care in pleural mesothelioma. Further randomised studies are needed of combinations of MesoPher and immune checkpoint therapy, which might increase efficacy without adding major toxicities. FUNDING: Amphera BV and EU HORIZON.

A Time-Varying Dynamic Partial Credit Model to Analyze Polytomous and Multivariate Time Series Data.

The accessibility to electronic devices and the novel statistical methodologies available have allowed researchers to comprehend psychological processes at the individual level. However, there are still great challenges to overcome as, in many cases, collected data are more complex than the available models are able to handle. For example, most methods assume that the variables in the time series are measured on an interval scale, which is not the case when Likert-scale items were used. Ignoring the scale of the variables can be problematic and bias the results. Additionally, most methods also assume that the time series are stationary, which is rarely the case. To tackle these disadvantages, we propose a model that combines the partial credit model (PCM) of the item response theory framework and the time-varying autoregressive model (TV-AR), which is a popular model used to study psychological dynamics. The proposed model is referred to as the time-varying dynamic partial credit model (TV-DPCM), which allows to appropriately analyze multivariate polytomous data and nonstationary time series. We test the performance and accuracy of the TV-DPCM in a simulation study. Lastly, by means of an example, we show how to fit the model to empirical data and interpret the results.

The Crit coefficient in Mokken scale analysis: a simulation study and an application in quality-of-life research.

PURPOSE: In Mokken scaling, the Crit index was proposed and is sometimes used as evidence (or lack thereof) of violations of some common model assumptions. The main goal of our study was twofold: To make the formulation of the Crit index explicit and accessible, and to investigate its distribution under various measurement conditions. METHODS: We conducted two simulation studies in the context of dichotomously scored item responses. We manipulated the type of assumption violation, the proportion of violating items, sample size, and quality. False positive rates and power to detect assumption violations were our main outcome variables. Furthermore, we used the Crit coefficient in a Mokken scale analysis to a set of responses to the General Health Questionnaire (GHQ-12), a self-administered questionnaire for assessing current mental health. RESULTS: We found that the false positive rates of Crit were close to the nominal rate in most conditions, and that power to detect misfit depended on the sample size, type of violation, and number of assumption-violating items. Overall, in small samples Crit lacked the power to detect misfit, and in larger samples power differed considerably depending on the type of violation and proportion of misfitting items. Furthermore, we also found in our empirical example that even in large samples the Crit index may fail to detect assumption violations. DISCUSSION: Even in large samples, the Crit coefficient showed limited usefulness for detecting moderate and severe violations of monotonicity. Our findings are relevant to researchers and practitioners who use Mokken scaling for scale and questionnaire construction and revision.

Searching for the optimal number of response alternatives for the distress scale of the four-dimensional symptom questionnaire.

BACKGROUND: The Four-Dimensional Symptom Questionnaire (4DSQ) is a self-report questionnaire designed to measure distress, depression, anxiety, and somatization. Prior to computing scale scores from the item scores, the three highest response alternatives ('Regularly', 'Often', and 'Very often or constantly present') are usually collapsed into one category to reduce the influence of extreme responding on item- and scale scores. In this study, we evaluate the usefulness of this transformation for the distress scale based on a variety of criteria. METHODS: Specifically, by using the Graded Response Model, we investigated the effect of this transformation on model fit, local measurement precision, and various indicators of the scale's validity to get an indication on whether the current practice of recoding should be advocated or not. In particular, the effect on the convergent- (operationalized by the General Health Questionnaire and the Maastricht Questionnaire), divergent- (operationalized by the Neuroticism scale of the NEO-FFI), and predictive validity (operationalized as obtrusion with daily chores and activities, the Biographical Problem list and the Utrecht Burnout Scale) of the distress scale was investigated. RESULTS: Results indicate that recoding leads to (i) better model fit as indicated by lower mean probabilities of exact test statistics assessing item fit, (ii) small (<.02) losses in the sizes of various validity coefficients, and (iii) a decrease (DIFF (SE's) = .10-.25) in measurement precision for medium and high levels of distress. CONCLUSIONS: For clinical applications and applications in longitudinal research, the current practice of recoding should be avoided because recoding decreases measurement precision for medium and high levels of distress. It would be interesting to see whether this advice also holds for the three other domains of the 4DSQ.

Person-fit feedback on inconsistent symptom reports in clinical depression care.

BACKGROUND: Depressive patients can present with complex and different symptom patterns in clinical care. Of these, some may report patterns that are inconsistent with typical patterns of depressive symptoms. This study aimed to evaluate the validity of person-fit statistics to identify inconsistent symptom reports and to assess the clinical usefulness of providing clinicians with person-fit score feedback during depression assessment. METHODS: Inconsistent symptom reports on the Inventory of Depressive Symptomatology Self-Report (IDS-SR) were investigated quantitatively with person-fit statistics for both intake and follow-up measurements in the Groningen University Center of Psychiatry (n = 2036). Subsequently, to investigate the causes and clinical usefulness of on-the-fly person-fit alerts, qualitative follow-up assessments were conducted with three psychiatrists about 20 of their patients that were randomly selected. RESULTS: Inconsistent symptom reports at intake (12.3%) were predominantly characterized by reporting of severe symptoms (e.g. psychomotor slowing) without mild symptoms (e.g. irritability). Person-fit scores at intake and follow-up were positively correlated (r = 0.45). Qualitative interviews with psychiatrists resulted in an explanation for the inconsistent response behavior (e.g. complex comorbidity, somatic complaints, and neurological abnormalities) for 19 of 20 patients. Psychiatrists indicated that if provided directly after the assessment, a person-fit alert would have led to new insights in 60%, and be reason for discussion with the patient in 75% of the cases. CONCLUSIONS: Providing clinicians with automated feedback when inconsistent symptom reports occur is informative and can be used to support clinical decision-making.

Identifying levels of general distress in first line mental health services: can GP- and eHealth clients' scores be meaningfully compared?

BACKGROUND: The Four-Dimensional Symptom Questionnaire (4DSQ) (Huisarts Wetenschap 39: 538-47, 1996) is a self-report questionnaire developed in the Netherlands to distinguish non-specific general distress from depression, anxiety, and somatization. This questionnaire is often used in different populations and settings and there is a paper-and-pencil and computerized version. METHODS: We used item response theory to investigate whether the 4DSQ measures the same construct (structural equivalence) in the same way (scalar equivalence) in two samples comprised of primary mental health care attendees: (i) clients who visited their General Practitioner responded to the 4DSQ paper-and-pencil version, and (ii) eHealth clients responded to the 4DSQ computerized version. Specifically, we investigated whether the distress items functioned differently in eHealth clients compared to General Practitioners' clients and whether these differences lead to substantial differences at scale level. RESULTS: Results showed that in general structural equivalence holds for the distress scale. This means that the distress scale measures the same construct in both General Practitioners' clients and eHealth clients. Furthermore, although eHealth clients have higher observed distress scores than General Practitioners' clients, application of a multiple group generalized partial credit response model suggests that scalar equivalence holds. CONCLUSIONS: The same cutoff scores can be used for classifying respondents as having low, moderate and high levels of distress in both settings.

Investigating the Practical Consequences of Model Misfit in Unidimensional IRT Models.

In this article, the practical consequences of violations of unidimensionality on selection decisions in the framework of unidimensional item response theory (IRT) models are investigated based on simulated data. The factors manipulated include the severity of violations, the proportion of misfitting items, and test length. The outcomes that were considered are the precision and accuracy of the estimated model parameters, the correlations of estimated ability ([Formula: see text]) and number-correct ([Formula: see text]) scores with the true ability ([Formula: see text]), the ranks of the examinees and the overlap between sets of examinees selected based on either [Formula: see text], [Formula: see text], or [Formula: see text] scores, and the bias in criterion-related validity estimates. Results show that the [Formula: see text] values were unbiased by violations of unidimensionality, but their precision decreased as multidimensionality and the proportion of misfitting items increased; the estimated item parameters were robust to violations of unidimensionality. The correlations between [Formula: see text], [Formula: see text], and [Formula: see text] scores, the agreement between the three selection criteria, and the accuracy of criterion-related validity estimates are all negatively affected, to some extent, by increasing levels of multidimensionality and the proportion of misfitting items. However, removing the misfitting items only improved the results in the case of severe multidimensionality and large proportion of misfitting items, and deteriorated them otherwise.

Assessment of fit of the time-varying dynamic partial credit model using the posterior predictive model checking method.

Several new models based on item response theory have recently been suggested to analyse intensive longitudinal data. One of these new models is the time-varying dynamic partial credit model (TV-DPCM; Castro-Alvarez et al., Multivariate Behavioral Research, 2023, 1), which is a combination of the partial credit model and the time-varying autoregressive model. The model allows the study of the psychometric properties of the items and the modelling of nonlinear trends at the latent state level. However, there is a severe lack of tools to assess the fit of the TV-DPCM. In this paper, we propose and develop several test statistics and discrepancy measures based on the posterior predictive model checking (PPMC) method (PPMC; Rubin, The Annals of Statistics, 1984, 12, 1151) to assess the fit of the TV-DPCM. Simulated and empirical data are used to study the performance of and illustrate the effectiveness of the PPMC method.

Assessing the credibility of a drug's effects: identification and judgment of uncertainty by the Dutch Medicines Evaluation Board.

Medicine regulators need to judge whether a drug's favorable effects outweigh its unfavorable effects based on a dossier submitted by an applicant, such as a pharmaceutical company. Because scientific knowledge is inherently uncertain, regulators also need to judge the credibility of these effects by identifying and evaluating uncertainties. We performed an ethnographic study of assessment procedures at the Dutch Medicines Evaluation Board (MEB) and describe how regulators evaluate the credibility of an applicant's claims about the benefits and risks of a drug in practice. Our analysis shows that regulators use an investigative approach, which illustrates the effort required to identify uncertainties. Moreover, we show that regulators' expectations about the presentation, the design, and the results of studies can shape how they perceive a medicine's dossier. We highlight the importance of regulatory experience and expertise in the identification and evaluation of uncertainties. In light of our observations, we provide two recommendations to reduce avoidable uncertainty: less reliance on evidence generated by the applicant; and better communication about, and enforcement of, regulatory frameworks toward drug developers.

A uniform approach for advancing athlete assessment: A tutorial on the Lens Model.

In athlete assessment, coaches or scouts typically judge athletes by observing and combining information about their attributes. However, how accurate is the expert's eye in combining this information, and can its accuracy be improved? To address these questions, this paper introduces the Lens Model, a framework for studying human judgment that has been widely successful in other performance domains. Since the framework offers both theoretical and practical benefits and is new to sports scientists and practitioners, our paper is presented in the form of a tutorial. First, we discuss the need for the Lens Model in sports; second, we demonstrate its proven value outside of sports. Third, we provide a conceptual explanation of the Lens Model, detailing, among other aspects, how experts' judgmental policies can be modeled and how judgmental accuracy can be determined and evaluated. This is followed by an empirical example: a study on the judgments of soccer scouts, along with suggestions to improve their accuracy. To inspire further Lens Model research across sports, we conclude with prospective research directions.

Strength of statistical evidence for the efficacy of cancer drugs: a Bayesian reanalysis of randomized trials supporting Food and Drug Administration approval.

OBJECTIVES: To quantify the strength of statistical evidence of randomized controlled trials (RCTs) for novel cancer drugs approved by the Food and Drug Administration in the last 2 decades. STUDY DESIGN AND SETTING: We used data on overall survival (OS), progression-free survival, and tumor response for novel cancer drugs approved for the first time by the Food and Drug Administration between January 2000 and December 2020. We assessed strength of statistical evidence by calculating Bayes factors (BFs) for all available endpoints, and we pooled evidence using Bayesian fixed-effect meta-analysis for indications approved based on 2 RCTs. Strength of statistical evidence was compared among endpoints, approval pathways, lines of treatment, and types of cancer. RESULTS: We analysed the available data from 82 RCTs corresponding to 68 indications supported by a single RCT and 7 indications supported by 2 RCTs. Median strength of statistical evidence was ambiguous for OS (BF = 1.9; interquartile range [IQR] 0.5-14.5), and strong for progression-free survival (BF = 24,767.8; IQR 109.0-7.3 × 106) and tumor response (BF = 113.9; IQR 3.0-547,100). Overall, 44 indications (58.7%) were approved without clear statistical evidence for OS improvements and 7 indications (9.3%) were approved without statistical evidence for improvements on any endpoint. Strength of statistical evidence was lower for accelerated approval compared to nonaccelerated approval across all 3 endpoints. No meaningful differences were observed for line of treatment and cancer type. This analysis is limited to statistical evidence. We did not consider nonstatistical factors (eg, risk of bias, quality of the evidence). CONCLUSION: BFs offer novel insights into the strength of statistical evidence underlying cancer drug approvals. Most novel cancer drugs lack strong statistical evidence that they improve OS, and a few lack statistical evidence for efficacy altogether. These cases require a transparent and clear explanation. When evidence is ambiguous, additional postmarketing trials could reduce uncertainty.

Measuring individual significant change on the Beck Depression Inventory-II through IRT-based statistics.

Several researchers have emphasized that item response theory (IRT)-based methods should be preferred over classical approaches in measuring change for individual patients. In the present study we discuss and evaluate the use of IRT-based statistics to measure statistical significant individual change on the Beck Depression Inventory-II (BDI-II, Beck, Steer, & Brown, 1996). We compare results obtained with a simple IRT-based statistical test (Z-test) to those obtained with the Reliable Change Index (RCI) in a sample of clinical outpatients. Mean group differences between the Z-test and the RCI were similar, but for some individuals change classifications differed. Differences were most evident for change scores within the lower range of depression scores. We show that this may have consequences for the measurement of individual change in psychotherapy outcome research and clinical practice.

Item response theory: how Mokken scaling can be used in clinical practice.

AIMS: To demonstrate the principles and application of Mokken scaling. BACKGROUND: The history and development of Mokken scaling is described, some examples of applications are given, and some recent development of the method are summarised. DESIGN: Secondary analysis of data obtained by cross-sectional survey methods, including self-report and observation. METHODS: Data from the Edinburgh Feeding Evaluation in Dementia scale and the Townsend Functional Ability Scale were analysed using the Mokken scaling procedure within the 'R' statistical package. Specifically, invariant item ordering (the extent to which the order of the items in terms of difficulty was the same for all respondents whatever their total scale score) was studied. RESULTS: The Edinburgh Feeding Evaluation in Dementia scale and the Townsend Functional Ability Scale showed no violations of invariant item ordering, although only the Townsend Functional Ability Scale showed a medium accuracy. CONCLUSION: Mokken scaling is an established method for item response theory analysis with wide application in the social sciences. It provides psychometricians with an additional tool in the development of questionnaires and in the study of individuals and their responses to latent traits. Specifically, with regard to the analyses conducted in this study, the Edinburgh Feeding Evaluation in Dementia scale requires further development and study across different levels of severity of dementia and feeding difficulty. RELEVANCE TO CLINICAL PRACTICE: Good scales are required for assessment in clinical practice and the present paper shows how a relatively recently developed method for analysing Mokken scales can contribute to this. The two scales used as examples for analysis are highly clinically relevant.

Using structural equation modeling to study traits and states in intensive longitudinal data.

Traditionally, researchers have used time series and multilevel models to analyze intensive longitudinal data. However, these models do not directly address traits and states which conceptualize the stability and variability implicit in longitudinal research, and they do not explicitly take into account measurement error. An alternative to overcome these drawbacks is to consider structural equation models (state-trait SEMs) for longitudinal data that represent traits and states as latent variables. Most of these models are encompassed in the latent state-trait (LST) theory. These state-trait SEMs can be problematic when the number of measurement occasions increases. As they require the data to be in wide format, these models quickly become overparameterized and lead to nonconvergence issues. For these reasons, multilevel versions of state-trait SEMs have been proposed, which require the data in long format. To study how suitable state-trait SEMs are for intensive longitudinal data, we carried out a simulation study. We compared the traditional single level to the multilevel version of three state-trait SEMs. The selected models were the multistate-singletrait (MSST) model, the common and unique trait-state (CUTS) model, and the trait-state-occasion (TSO) model. Furthermore, we also included an empirical application. Our results indicated that the TSO model performed best in both the simulated and the empirical data. To conclude, we highlight the usefulness of state-trait SEMs to study the psychometric properties of the questionnaires used in intensive longitudinal data. Yet, these models still have multiple limitations, some of which might be overcome by extending them to more general frameworks. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Education increases decision-rule use: An investigation of education and incentives to improve decision making.

Robust scientific evidence shows that human performance predictions are more valid when information is combined mechanically (with a decision rule) rather than holistically (in the decision-maker's mind). Yet, information is often combined holistically in practice. One reason is that decision makers lack the knowledge of evidence-based decision making. In a performance prediction task, we tested whether watching an educational video on evidence-based decision making increased decision-makers' use of a decision rule and their prediction accuracy immediately after the manipulation and a month later. Furthermore, we manipulated whether participants earned incentives for accurate predictions. Existing research showed that incentives decrease decision-rule use and prediction accuracy. We hypothesized that this is the case for decision makers who did not receive educational information about evidence-based decision making, but that incentives increase decision-rule use and prediction accuracy for participants who received educational information. Our results showed that educational information increased decision-rule use. This resulted in increased prediction accuracy, but only immediately after receiving the educational information. In contrast to the existing literature, incentives slightly increased decision-rule use. We did not find evidence that this effect was larger for educated participants. Providing decision makers with educational information may be effective to increase decision-rule use in practice. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

How soccer scouts identify talented players.

Scouts of soccer clubs are often the first to identify talented players. However, there is a lack of research on how these scouts assess and predict overall soccer performance. Therefore, we conducted a large-scaled study to examine the process of talent identification among 125 soccer scouts. Through an online self-report questionnaire, scouts were asked about (1) the players' age at which they can predict players' soccer performance, (2) the attributes they consider relevant, and (3) the extent to which they predict performance in a structured manner. The most important results are as follows. First, scouts who observed 12-year-old and younger players perceived they could predict at older ages (13.6 years old, on average) whether a player has the potential to become a professional soccer player. This suggests that scouts are aware of the idea that early indicators of later performance are often lacking, yet do advise on selection of players at younger ages. Second, when identifying talented players, scouts considered more easily observable attributes, such as technical attributes. However, scouts described these often in a broad sense rather than in terms of specific predictors of future performance. Finally, scouts reported that they assess attributes of players in a structured manner. Yet, they ultimately based their prediction (i.e. final score) on an intuitive integration of different performance attributes, which is a suboptimal strategy according to existing literature. Taken together, these outcomes provide specific clues to improve the reliability and validity of the scouting process. HighlightsBased on a large sample of soccer scouts, we examine three issues that are important in the process of identifying talented soccer players: The age at which good performance predictions can be made, which attributes are relevant predictors, and how performance predictions are formed.Scouts who observe players in young age cohorts believe that the age at which they can predict performance is older than the players they typically scout, suggesting that they are aware that early indicators of performance are often lacking.Technical performance attributes are considered as most important performance predictors by scouts, but these are often described in a broad - rather than specific - sense.Scouts indicate that they predict performance in a structured manner, but form their overall performance prediction on an intuitive integration of different performance attributes, which can be a suboptimal approach.

Natural history and long-term testicular growth of acquired undescended testis after spontaneous descent or pubertal orchidopexy.

OBJECTIVE: To assess prospectively the natural history and long-term testicular growth of acquired undescended testis (UDT) after spontaneous descent or pubertal orchidopexy in case of nondescent. PATIENTS AND METHODS: From 1996 until 2008, 391 boys with 464 acquired UDT were included in the study. In accordance with Dutch consensus on non-scrotal testes, spontaneous descent at puberty was awaited; if this did not take place, orchidopexy was performed at puberty. Acquired UDT was defined as a testis previously residing in the scrotum that can no longer be manipulated into a stable scrotal (high scrotal) or nonscrotal (inguinal, impalpable) position. After referral, testis position, testis volume and puberty stage were monitored annually until adolescence. Testis volume was assessed using an orchidometer and compared with the Dutch standard. All investigations were carried out by the same physician (W.H.). Of these boys, 84 (mean age 12.9 years, range 6.4-21.3) were also clinically assessed by a second physician (J.G.), unaware of the results of the first examination. In addition, these boys were assessed with testicular ultrasonography, carried out by both physicians. RESULTS: Currently the mean (range) follow-up is 4.7 (0.1-12.0) years, and 253 acquired UDT have reached the scrotum. In 196 of these 253 cases (77.5%), there was spontaneous descent at puberty (mean age at descent 12.9 years, range 9.8-16.9); in the other 57 cases (22.5%), pubertal orchidopexy was required due to nondescent; five cases required orchidectomy. Of the 494 testis volume measurements after spontaneous descent, 458 (92.7%) were at ≥10th centile for age, of which 311 (63.0%) were ≥50th centile, and 107 (21.7%) ≥90th centile. After pubertal orchidopexy for nondescent, of the 85 measurements, 79 (92.9%) were at ≥10th centile, 53 (62.4%) ≥50th centile and 12 (14.1%) ≥90th centile. In unilateral cases, after spontaneous descent 174 of the 294 (59.2%) retained testes were found to be smaller than their counterpart and 90 of 294 (30.6%) were equal in size. After pubertal orchidopexy in unilateral cases, 40 of the 51 (78.4%) testes were smaller, and nine (17.6%) were equal in size. There was a strong correlation between both investigators for the measurement of testicular volume by orchidometer, and for the main investigator (W.H.) between his measurements by ultrasonography and the Prader orchidometer. CONCLUSION: Acquired UDT has a 77.5% tendency of spontaneous descent at puberty. In nearly all cases, after spontaneous descent as well as after pubertal orchidopexy, long-term testicular growth is within the normal range.